pca_interpret: Colored Table to Help Interpretation of Principal Component...
In ggfacto: Graphs for Correspondence Analysis
pca_interpret R Documentation
Colored Table to Help Interpretation of Principal Component Analysis
Description
Colored Table to Help Interpretation of Principal Component Analysis
Usage
pca_interpret(res.pca, axes = 1:3)
Arguments
res.pca
The result of FactoMineR::PCA.
axes
The axes to print, as a numeric vector.
Value
A tibble of class tabxplor
Examples
data(mtcars, package = "datasets")
mtcars <- mtcars[1:7] |> dplyr::rename(weight = wt)
res.pca <- FactoMineR::PCA(mtcars, graph = FALSE)
pca_interpret(res.pca)
ggfacto documentation built on Oct. 3, 2024, 1:08 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| pca_interpret | R Documentation |
Colored Table to Help Interpretation of Principal Component Analysis
Description
Colored Table to Help Interpretation of Principal Component Analysis
Usage
pca_interpret(res.pca, axes = 1:3)
Arguments
res.pca |
The result of |
axes |
The axes to print, as a numeric vector. |
Value
A tibble of class tabxplor
Examples
data(mtcars, package = "datasets")
mtcars <- mtcars[1:7] |> dplyr::rename(weight = wt)
res.pca <- FactoMineR::PCA(mtcars, graph = FALSE)
pca_interpret(res.pca)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.